Oxfold: kinetic folding of RNA using stochastic context-free grammars and evolutionary information.
MOTIVATION:Many computational methods for RNA secondary structure prediction, and, in particular, for the prediction of a consensus structure of an alignment of RNA sequences, have been developed. Most methods, however, ignore biophysical factors, such as the kinetics of RNA folding; no current impl...
Main Authors: | , , , , , , |
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Format: | Journal article |
Language: | English |
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Oxford University Press (OUP)
2013
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_version_ | 1826260970591223808 |
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author | Anderson, JWJ Haas, PA Mathieson, L-A Volynkin, V Lyngsø, R Tataru, P Hein, J |
author_facet | Anderson, JWJ Haas, PA Mathieson, L-A Volynkin, V Lyngsø, R Tataru, P Hein, J |
author_sort | Anderson, JWJ |
collection | OXFORD |
description | MOTIVATION:Many computational methods for RNA secondary structure prediction, and, in particular, for the prediction of a consensus structure of an alignment of RNA sequences, have been developed. Most methods, however, ignore biophysical factors, such as the kinetics of RNA folding; no current implementation considers both evolutionary information and folding kinetics, thus losing information that, when considered, might lead to better predictions. RESULTS:We present an iterative algorithm, Oxfold, in the framework of stochastic context-free grammars, that emulates the kinetics of RNA folding in a simplified way, in combination with a molecular evolution model. This method improves considerably on existing grammatical models that do not consider folding kinetics. Additionally, the model compares favourably to non-kinetic thermodynamic models. |
first_indexed | 2024-03-06T19:14:11Z |
format | Journal article |
id | oxford-uuid:17c7f78a-bcd1-4eaf-b485-ff2bf8a2b32b |
institution | University of Oxford |
language | English |
last_indexed | 2024-03-06T19:14:11Z |
publishDate | 2013 |
publisher | Oxford University Press (OUP) |
record_format | dspace |
spelling | oxford-uuid:17c7f78a-bcd1-4eaf-b485-ff2bf8a2b32b2022-03-26T10:39:27ZOxfold: kinetic folding of RNA using stochastic context-free grammars and evolutionary information.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:17c7f78a-bcd1-4eaf-b485-ff2bf8a2b32bEnglishSymplectic ElementsOxford University Press (OUP)2013Anderson, JWJHaas, PAMathieson, L-AVolynkin, VLyngsø, RTataru, PHein, JMOTIVATION:Many computational methods for RNA secondary structure prediction, and, in particular, for the prediction of a consensus structure of an alignment of RNA sequences, have been developed. Most methods, however, ignore biophysical factors, such as the kinetics of RNA folding; no current implementation considers both evolutionary information and folding kinetics, thus losing information that, when considered, might lead to better predictions. RESULTS:We present an iterative algorithm, Oxfold, in the framework of stochastic context-free grammars, that emulates the kinetics of RNA folding in a simplified way, in combination with a molecular evolution model. This method improves considerably on existing grammatical models that do not consider folding kinetics. Additionally, the model compares favourably to non-kinetic thermodynamic models. |
spellingShingle | Anderson, JWJ Haas, PA Mathieson, L-A Volynkin, V Lyngsø, R Tataru, P Hein, J Oxfold: kinetic folding of RNA using stochastic context-free grammars and evolutionary information. |
title | Oxfold: kinetic folding of RNA using stochastic context-free grammars and evolutionary information. |
title_full | Oxfold: kinetic folding of RNA using stochastic context-free grammars and evolutionary information. |
title_fullStr | Oxfold: kinetic folding of RNA using stochastic context-free grammars and evolutionary information. |
title_full_unstemmed | Oxfold: kinetic folding of RNA using stochastic context-free grammars and evolutionary information. |
title_short | Oxfold: kinetic folding of RNA using stochastic context-free grammars and evolutionary information. |
title_sort | oxfold kinetic folding of rna using stochastic context free grammars and evolutionary information |
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